Cell migration analysis: Segmenting scratch assay images with level sets and support vector machines

Cell migration assessment is often done by scratch assay experiments for which quantitative evaluations are usually performed manually. Here we present an automatic analysis pipeline detecting scratch boundaries and measuring areas based on level sets. We extend non-PDE level sets for topology-preservation and use an entropy-based energy functional. This approach by design segments a scratch in every image, hence, we employ support vector machines to identify images showing no scratch at all. Compared to other algorithms our approach, implemented as ImageJ plugin, relies on a minimal set of parameters. Experimental evaluations show the high quality of results and their suitability for biomedical investigations.

► We developed a fully automatic pipeline for the analysis of scratch assays images. ► A topology preservation method is devised for segmentation with non-PDE level sets. ► We use support vector machines to classify images into containing a scratch or not. ► Only a minimal set of configuration parameters is needed. ► Obtained results are shown to be robust and reliable.